Developing a b-tagging algorithm using soft muons at level-3 for the DO detector at Fermilab

The current data-taking phase of the DO detector at Fermilab, called Run II, is designed to aid the search for the Higgs Boson. The neutral Higgs is postulated to have a mass of 117 GeV. One of the channels promising the presence of this hypothetical particle is through the decay of b-quark into a muon. The process of identifying a b-quark in a jet using muon as a reference is b-tagging with a muon tag.; At the current data taking and analysis rate, it will take long to reach the process of identifying valid events. The triggering mechanism of the experiment, consisting of 3 levels of combined hardware, firmware and software writes final physics events at the rate of 50 Hz to data disks, with Level-3 alone accounting for the reduction from 1 kHz to 50 Hz. This large rejection is achieved through algorithms implemented in the search for key physics processes.; The work presented in this dissertation is the development of a fast b-tagging algorithm using central-matched muons, called L3FBTagMU. Additional tools such as the impact parameter tracks and calorimeter jets have been used to tag B jets. The dR or the differential increment in cone radius is the most significant variable introduced. Plots within thresholds of dR for both Z → bb Monte Carlo and monitor stream data show similar efficiency trends when checked against other parameters.; The differential efficiencies saturate at dR within 0.5 to 0.7 range. Differential bins of 0.1 intervals project an overall efficiency of tagging a b-jet in any event is 17.25 in data. This is in good agreement with the theory.; The algorithm is currently running online and of line through the DO database repository. This work is primarily used by the b-id, B-Physics and Higgs Physics groups for their physics analysis wherein the above b-tagging efficiency serves as a crucial tool. The prospect for optimizing the physics potential using this algorithm is very promising for current and future analyses.